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Novel Algorithm for Efficient Distribution of Molecular Docking Calculations

  • Luigi Di Biasi
  • Roberto Fino
  • Rosaura Parisi
  • Lucia Sessa
  • Giuseppe Cattaneo
  • Alfredo De Santis
  • Pio Iannelli
  • Stefano PiottoEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 587)

Abstract

Molecular docking is a computational method to study the formation of intermolecular complexes between two molecules. In drug discovery, it is employed to estimate the binding between a small ligand (the drug candidate), and a protein of known three-dimensional structure. Docking is becoming a standard part of workflow in drug discovery. Recently, we have used the software VINA, a de facto standard in molecular docking, to perform extensive docking analysis. Unfortunately, performing a successful blind docking procedure requires large computational resources that can be obtained by the use of clusters or dedicated grid. Here we present a new tool to distribute efficiently a molecular docking calculation onto a grid changing the distribution paradigm: we define portions on the protein surface, named hotspots, and the grid will perform a local docking for each region. Performance studies have been conducted via the software GRIMD.

Keywords

Molecular Docking Markov Chain Monte Carlo Method Docking Software Blind Docking Conservation Weight 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was partially supported by the “Data-Driven Genomic Computing (GenData 2020)” PRIN project (2013–2015), funded by the Italian Ministry of the University and Research (MIUR).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Luigi Di Biasi
    • 1
    • 2
  • Roberto Fino
    • 1
  • Rosaura Parisi
    • 1
  • Lucia Sessa
    • 1
  • Giuseppe Cattaneo
    • 2
  • Alfredo De Santis
    • 2
  • Pio Iannelli
    • 1
  • Stefano Piotto
    • 1
    Email author
  1. 1.Department of PharmacyUniversity of SalernoFiscianoItaly
  2. 2.Department of InformaticsUniversity of SalernoFiscianoItaly

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